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| 앵커 기반 최소 임상적 중요 변화량(Minimal Important Difference)× | 척도 개발을 위한 요인 분석× | |
|---|---|---|
| 분야 | 심리측정학 | 심리측정학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 1989 | 1947 |
| 창시자≠ | Guyatt, Jaeschke, and Singer | Louis Thurstone |
| 유형≠ | Minimal clinically important difference estimation | Exploratory factor analysis methodology |
| 원전≠ | Jaeschke, R., Singer, J., & Guyatt, G. H. (1989). Measurement of health status: Ascertaining the minimal clinically important difference. Controlled Clinical Trials, 10(4), 407-415. DOI ↗ | Thurstone, L. L. (1947). Multiple-Factor Analysis: A Development and Expansion of the Vectors of Mind (2nd ed.). Chicago: University of Chicago Press. ISBN: 9780226797557 |
| 별칭≠ | MCID, Minimal clinically important difference, Anchor-based MCID, Minimal important change | Exploratory factor analysis, EFA for scale development, Factorial structure analysis |
| 관련≠ | 4 | 5 |
| 요약≠ | The anchor-based method for establishing Minimal Clinically Important Difference (MCID) is a technique for determining the smallest change in a patient-reported outcome (PRO) that patients or clinicians perceive as meaningful or important. Pioneered by Guyatt, Jaeschke, and Singer in 1989, this approach anchors changes in outcome scores to external clinically meaningful events or judgments, enabling researchers and clinicians to interpret whether treatment effects represent real, patient-relevant improvements. | Exploratory factor analysis (EFA) is a statistical method for discovering the underlying dimensional structure of a set of items or variables. Pioneered by Louis Thurstone in the mid-20th century, EFA is widely used to develop and validate psychometric scales by identifying groups of items that correlate together, thereby revealing latent dimensions of the construct being measured. The method reduces item sets to a smaller number of interpretable factors. |
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